Typically, two's complement is chosen to represent numbers since arithmetic operations of addition and subtraction are easy to perform. However, due to sign extension, an arithmetic operation for small dynamic dat...
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Typically, two's complement is chosen to represent numbers since arithmetic operations of addition and subtraction are easy to perform. However, due to sign extension, an arithmetic operation for small dynamic data ranges may require switching power in the entire word length. Herein, we develop a two's complement adder with the dynamic-range determination and sign-extension units to reduce power consumption. According to the actual data range by minimizing sign-extension bits, only partial functional blocks of an adder are active to generate a final result of which sign bit is then extended to match the original word length. Experimental results demonstrate that our 32-bit carry-lookahead adder has 22.9% power reduction than the conventional one while dynamic ranges of input data are the Gaussian distribution with a mean of 16 bits and a standard deviation of 8 bits.
We analyze the convergence behavior of the CRLS-SA algorithm for inverse filtering. The CRLS-SA is a cascade adaptive filter based on the RLS algorithm, with each section adapted independently based on global minimiza...
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We analyze the convergence behavior of the CRLS-SA algorithm for inverse filtering. The CRLS-SA is a cascade adaptive filter based on the RLS algorithm, with each section adapted independently based on global minimization. The subsection adaptation results in reduced computational complexity. The rate of convergence is evaluated based on the convergence time constant defined as the ratio of condition number and sensitivity. The smaller the convergence time constant, the faster the structure converges. Analysis and simulation explain and show that CRLS-SA exhibits faster convergence than the direct form RLS adaptive filter for speech type signals.
A microarchitecture of a processor named RAPTOR is described. RAPTOR is a single chip multiprocessor developed for exploiting thread-level parallelism. RAPTOR includes four identical processors, a graphics coprocessor...
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A microarchitecture of a processor named RAPTOR is described. RAPTOR is a single chip multiprocessor developed for exploiting thread-level parallelism. RAPTOR includes four identical processors, a graphics coprocessor, and an external cache controller. Each processor has a 16 KB primary cache and implements SPARC version 9 instruction set architecture. The external cache controller provides direct connection to a large external second level cache. RAPTOR is designed as a building block of multiprocessor systems such as symmetric multiprocessor machines.
We propose the adaptive cascade recursive least squares (CRLS-SA) algorithm for the estimation of linear prediction, or AR model, coefficients. The CRLS-SA algorithm features low computational complexity since each se...
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Currently, many multimedia or continuous media server system is under development on top of either workstations or high-end PCs clustered with high speed networking facilities. In this paper we introduce Crown, a cont...
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ISBN:
(纸本)0818672250
Currently, many multimedia or continuous media server system is under development on top of either workstations or high-end PCs clustered with high speed networking facilities. In this paper we introduce Crown, a continuous media server on clustered high performance PCs with Myrinet, fast network switching equipment, and then address CrownFS, a file system on top of Crown, to offer continuous media streams to many subscribers at the same time. For easy and rapid tuning of the performance of CrownFS, we prototyped it. Prototyping requires less efforts and costs than direct implementation. Also, more reliable system optimization is obtainable rather than simulation. By using the prototype, we measured the scalability of CrownFS according to disk access strategies.
We propose the adaptive cascade recursive least squares (CRLS-SA) algorithm for the estimation of linear prediction, or AR model, coefficients. The CRLS-SA algorithm features low computational complexity since each se...
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We propose the adaptive cascade recursive least squares (CRLS-SA) algorithm for the estimation of linear prediction, or AR model, coefficients. The CRLS-SA algorithm features low computational complexity since each section is adapted independently from the other sections. It is shown that the CRLS-SA algorithm can yield AR coefficient estimates closer to the true values, for some known signals, than the widely used autocorrelation method. The CRLS-SA converges faster to the true values of the model, which is critically important for estimation from short data records. While the computational effort of CRLS-SA is a factor of 3 to 4 higher than that for the autocorrelation method, the improvement in performance yields a viable alternative for a number of applications.
Software reengineering for object-oriented rearchitecturing offers an exciting opportunity in migrating old legacy systems to evolvable systems in a disciplined manner. In the twofold-strategy software reengineering f...
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ISBN:
(纸本)0818685859
Software reengineering for object-oriented rearchitecturing offers an exciting opportunity in migrating old legacy systems to evolvable systems in a disciplined manner. In the twofold-strategy software reengineering for object-oriented rearchitecturing, one of the problems to be solved is to derive a proper object-oriented model from the output of reverse engineering and the output of forward engineering. In general, the outputs of forward and reverse engineering can be inconsistent in their abstract levels, the amount of design information, naming conventions, and structures. In this paper we present an Object-oriented model Refinement Technique (ORT) to build a final object model in the twofold-strategy software reengineering. We first organize the information gained from reverse engineering into specification information tree, and then compare the entities in the specification information tree with the information from forward engineering using tree-structured data dictionary to produce the final model. We demonstrate the usability of ORT by an example.
To enhance the effectiveness of Thai text retrieval system, we need a significant improvement in automatic indexing. This paper is intended to provide the application of statistical and natural language processing tec...
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To enhance the effectiveness of Thai text retrieval system, we need a significant improvement in automatic indexing. This paper is intended to provide the application of statistical and natural language processing techniques to obtain multilevel content identifiers: phrasal level, single term level and conceptual level. These multilevel indices will cover a very wide range of document retrieval without degradation of system performance. Automatic multilevel indexing for Thai text requires three processes: lexical token identification, phrase identification and extraction, and multilevel index generation. The results give a significant benefit both in precision and recall.
Thai text retrieval systems always involve documents that use loan words (borrowed from foreign language), especially in the area of science and engineering. This paper describes an algorithmic approach to backward ma...
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Thai text retrieval systems always involve documents that use loan words (borrowed from foreign language), especially in the area of science and engineering. This paper describes an algorithmic approach to backward machine transliteration aimed at improving the retrieval process. The approach consists of two main steps: identifying loan words and back transliterating. The model of backward transliteration works successfully at approximately 95% including phonetic equivalent.
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